4.8 Article

Multireference Frame Based Open-Phase Fault Modeling and Control for Asymmetrical Six-Phase Interior Permanent Magnet Motors

Journal

IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 36, Issue 10, Pages 11712-11725

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2021.3072947

Keywords

Windings; Permanent magnet motors; Synchronous motors; Torque; Induction motors; Inductance; Stator windings; Asymmetrical six-phase; fault-tolerant control; interior permanent magnet motor (IPMM); maximum torque per ampere (MTPA); multireference frame; open-phase fault

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This article explores the modeling and control strategy of a six-phase asymmetric interior permanent magnet motor based on a multireference frame under single open-phase fault. By introducing dual dq-axis frame and dual-direction rotating frame, the fault-tolerant operation and control schemes are successfully developed, demonstrating the effectiveness of the proposed approach through experiments in both steady and transient scenarios.
Multireference frame based asymmetric six-phase interior permanent magnet motor modeling and control strategy under single open-phase fault are investigated in this article. The motor modeling under healthy operation is firstly established based on a dual dq-axis synchronous rotating frame. With this dual dq-axis frame, the motor modeling considering the magnetic saturation effect under open-phase fault has been derived. By introducing a dual-direction rotating frame, the stator current under single open-phase fault can be treated as the sum of a positive current sequence and a negative current sequence. With this dual-direction rotating frame, the two current sequences can be transformed into two dc components for fault-tolerant operation. Fault-tolerant control schemes with maximum torque per ampere for copper loss minimization and torque maximization are developed, respectively. Finally, the validity of the proposed modeling and control are evaluated by experiments under both steady and transient scenarios.

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